Preoperative Prediction Power of Imaging Methods for Microvascular Invasion in Hepatocellular Carcinoma: A Systemic Review and Meta-Analysis

被引:35
作者
Huang, Jiacheng [1 ,2 ,3 ]
Than, Wuwei [4 ]
Zhang, Lele [1 ,2 ,3 ]
Huang, Qiang [5 ]
Lin, Shengzhang [1 ]
Ding, Yong [4 ]
Liang, Wenjie [5 ]
Zheng, Shusen [1 ,2 ,3 ]
机构
[1] Zhejiang Univ, Affiliated Hosp 1, Coll Med, Dept Hepatobiliary & Pancreat Surg, Hangzhou, Peoples R China
[2] Zhejiang Univ, Affiliated Hosp 1, Coll Med, Collaborat Innovat Ctr Diag & Treatment Infect Di, Hangzhou, Peoples R China
[3] Zhejiang Univ, Key Lab Combined Multiorgan Transplantat, Coll Med, Affiliated Hosp 1,Minist Publ Hlth, Hangzhou, Peoples R China
[4] Zhejiang Univ, Coll Informat Sci & Elect Engn, Hangzhou, Peoples R China
[5] Zhejiang Univ, Affiliated Hosp 1, Coll Med, Dept Radiol, Hangzhou, Peoples R China
来源
FRONTIERS IN ONCOLOGY | 2020年 / 10卷
关键词
hepatocellular carcinoma; microvascular invasion; radiomics; conventional image; functional image; meta-analysis; RADIOMICS; TOMOGRAPHY; RECURRENCE; NOMOGRAM; RISK; MRI;
D O I
10.3389/fonc.2020.00887
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
Background: To compare the predictive power between radiomics and non-radiomics (conventional imaging and functional imaging methods) for preoperative evaluation of microvascular invasion (MVI) in hepatocellular carcinoma (HCC). Methods: Comprehensive publications were screened in PubMed, Embase, and Cochrane Library. Studies focusing on the discrimination values of imaging methods, including radiomics and non-radiomics methods, for MVI evaluation were included in our meta-analysis. Results: Thirty-three imaging studies with 5,462 cases, focusing on preoperative evaluation of MVI status in HCC, were included. The sensitivity and specificity of MVI prediction in HCC were 0.78 [95% confidence interval (CI): 0.75-0.80; I-2 = 70.7%] and 0.78 (95% CI: 0.76-0.81; I-2 = 0.0%) for radiomics, respectively, and were 0.73 (95% CI: 0.71-0.75; I-2 = 83.7%) and 0.82 (95% CI: 0.80-0.83; I-2 = 86.5%) for non-radiomics, respectively. The areas under the receiver operation curves for radiomics and non-radiomics to predict MVI status in HCC were 0.8550 and 0.8601, respectively, showing no significant difference. Conclusion: The imagingmethod is feasible to predict theMVI state of HCC. Radiomics method based on medical image data is a promising application in clinical practice and can provide quantifiable image features. With the help of these features, highly consistent prediction performance will be achieved in anticipation.
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页数:13
相关论文
共 59 条
[1]   Prediction of microvascular invasion of hepatocellular carcinoma using gadoxetic acid-enhanced MR and 18F-FDG PET/CT [J].
Ahn, Su Yeon ;
Lee, Jeong Min ;
Joo, Ijin ;
Lee, Eun Sun ;
Lee, Soo Jin ;
Cheon, Gi Jeong ;
Han, Joon Koo ;
Choi, Byung Ihn .
ABDOMINAL IMAGING, 2015, 40 (04) :843-851
[2]  
[Anonymous], 2018, LIV IM REP DAT SYST
[3]  
[Anonymous], 2019, EUR J NUCL MED MOL I, DOI DOI 10.1007/S00259-019-04592-1
[4]   A computed tomography radiogenomic biomarker predicts microvascular invasion and clinical outcomes in hepatocellular carcinoma [J].
Banerjee, Sudeep ;
Wang, David S. ;
Kim, Hyun J. ;
Sirlin, Claude B. ;
Chan, Michael G. ;
Korn, Ronald L. ;
Rutman, Aaron M. ;
Siripongsakun, Surachate ;
Lu, David ;
Imanbayev, Galym ;
Kuo, Michael D. .
HEPATOLOGY, 2015, 62 (03) :792-800
[5]   Hepatobiliary Cancers, Version 2.2019 Featured Updates to the NCCN Guidelines [J].
Benson, Al B., III ;
D'Angelica, Michael, I ;
Abbott, Daniel E. ;
Abrams, Thomas A. ;
Alberts, Steven R. ;
Anaya, Daniel A. ;
Anders, Robert ;
Are, Chandrakanth ;
Brown, Daniel ;
Chang, Daniel T. ;
Cloyd, Jordan ;
Covey, Anne M. ;
Hawkins, William ;
Iyer, Renuka ;
Jacob, Rojymon ;
Karachristos, Andreas ;
Kelley, R. Kate ;
Kim, Robin ;
Palta, Manisha ;
Park, James O. ;
Sahai, Vaibhav ;
Schefter, Tracey ;
Sicklick, Jason K. ;
Singh, Gagandeep ;
Sohal, Davendra ;
Stein, Stacey ;
Tian, G. Gary ;
Vauthey, Jean-Nicolas ;
Venook, Alan P. ;
Hammond, Lydia J. ;
Darlow, Susan D. .
JOURNAL OF THE NATIONAL COMPREHENSIVE CANCER NETWORK, 2019, 17 (04) :303-310
[6]   Hepatobiliary Cancers [J].
Benson, Al B., III ;
Abrams, Thomas A. ;
Ben-Josef, Edgar ;
Bloomston, P. Mark ;
Botha, Jean F. ;
Clary, Bryan M. ;
Covey, Anne ;
Curley, Steven A. ;
D'Angelica, Michael I. ;
Davila, Rene ;
Ensminger, William D. ;
Gibbs, John F. ;
Laheru, Daniel ;
Malafa, Mokenge P. ;
Marrero, Jorge ;
Meranze, Steven G. ;
Mulvihill, Sean J. ;
Park, James O. ;
Posey, James A. ;
Sachdev, Jasgit ;
Salem, Riad ;
Sigurdson, Elin R. ;
Sofocleous, Constantinos .
JOURNAL OF THE NATIONAL COMPREHENSIVE CANCER NETWORK, 2009, 7 (04) :350-391
[7]   Diffusion kurtosis imaging (DKI) of hepatocellular carcinoma: correlation with microvascular invasion and histologic grade [J].
Cao, Likun ;
Chen, Jie ;
Duan, Ting ;
Wang, Min ;
Jiang, Hanyu ;
Wei, Yi ;
Xia, Chunchao ;
Zhou, Xiaoyue ;
Yan, Xu ;
Song, Bin .
QUANTITATIVE IMAGING IN MEDICINE AND SURGERY, 2019, 9 (04) :590-602
[8]   Liver Imaging Reporting and Data System Category 5: MRI Predictors of Microvascular Invasion and Recurrence After Hepatectomy for Hepatocellular Carcinoma [J].
Chen, Jingbiao ;
Zhou, Jing ;
Kuang, Sichi ;
Zhang, Yao ;
Xie, Sidong ;
He, Bingjun ;
Deng, Ying ;
Yang, Hao ;
Shan, Qungang ;
Wu, Jun ;
Sirlin, Claude B. ;
Wang, Jin .
AMERICAN JOURNAL OF ROENTGENOLOGY, 2019, 213 (04) :821-830
[9]   Preoperative prediction of hepatocellular carcinoma tumour grade and micro-vascular invasion by means of artificial neural network: A pilot study [J].
Cucchetti, Alessandro ;
Piscaglia, Fabio ;
Grigioni, Antonia D'Errico ;
Ravaioli, Matteo ;
Cescon, Matteo ;
Zanello, Matteo ;
Grazi, Gian Luca ;
Golfieri, Rita ;
Grigioni, Walter Franco ;
Pinna, Antonio Daniele .
JOURNAL OF HEPATOLOGY, 2010, 52 (06) :880-888
[10]   Pretreatment 18F-FDG PET/CT Radiomics Predict Local Recurrence in Patients Treated with Stereotactic Body Radiotherapy for Early-Stage Non-Small Cell Lung Cancer: A Multicentric Study [J].
Dissaux, Gurvan ;
Visvikis, Dimitris ;
Da-ano, Ronrick ;
Pradier, Olivier ;
Chajon, Enrique ;
Barillot, Isabelle ;
Duverge, Loig ;
Masson, Ingrid ;
Abgral, Ronan ;
Ribeiro, Maria-Joao Santiago ;
Devillers, Anne ;
Pallardy, Amandine ;
Fleury, Vincent ;
Mahe, Marc-Andre ;
De Crevoisier, Renaud ;
Hatt, Mathieu ;
Schick, Ulrike .
JOURNAL OF NUCLEAR MEDICINE, 2020, 61 (06) :814-820